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Yolo returns uniformly placed detections (bboxes) with almost equal confidence. #1
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I get the samilar result, someone in the google group argue that maybe caused by the file read mode 'r' and 'rb' difference between linux and windows, but i try it and cannot make it work. |
Yes, that didn't work for me too. |
I find the problem, this is because the yolo.weights and yolo.cfg you download is up to date,but loading code in this project is out of date, so it cannot recognize some field name defined in yolo.cfg and just ignore it, this is the beginning of wrong weight load. |
Hm... Did you find a solution, too? If yes, then could you please share it with us? |
Hi, i also encountered the problem above. what i want to ask is that is there any hint or instruction on how to compile this project on windows? if we learned this method.so maybe we could create yolo-windows ourselves |
@2LOVES7 Hi, you can try this fork: https://github.com/AlexeyAB/yolo-windows I've just got this result on Windows 7 x64 with yolo.cfg from my fork and yolo.weights from here: http://pjreddie.com/media/files/yolo.weights |
Thanks! It works like charm. :D |
Can I compile your version of yolo using Visual Studio 2012? I tried with VS2012 and I have changed include and library paths to my opencv 3.0.0 and CUDA 7.5. I am getting linkage errors: 1>C:\Program Files (x86)\Microsoft Visual Studio 11.0\VC\include\limits(80): error : this declaration may not have extern "C" linkage this and many more like this for avgpool_layer_kernels.cu |
It can't be compiled using MSVS 2012 (v110) without code changes, because MSVS 2012 uses C89 standard of C, then must be declaring/initializing all local variables at the beginning of a code block (directly after an opening brace { ): http://stackoverflow.com/a/9903698/1558037 Otherwise there will be a lot of errors in lines like this: https://github.com/AlexeyAB/yolo-windows/blob/0bbef8e57ebd2d77d5ee46ed43e98db0c48c4cba/src/avgpool_layer.c#L8 About |
Is anyone succeeded in training YOLO over windows ? if so, could you please refer to that Fork? |
the training was working but the trained weights file have some issues. It On Thu 25 Aug, 2016, 11:23 anas-899, [email protected] wrote:
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@abhigarg yes, I also finished the training successfully but the output weight file is not detecting anything when I made that train on windows. |
I feel it has something to do with the way file is being written over On Thu 25 Aug, 2016, 11:31 anas-899, [email protected] wrote:
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@abhigarg I solved the saving weight issue. second: then the training on windows will save the weight correctly. |
thanks a lot .. I knew it would be somewhere there but could not find the I will try these changes and see at my end. On Fri 26 Aug, 2016, 11:23 anas-899, [email protected] wrote:
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Hi, i tried both of them but no success, on the @AlexeyAB fork when i try to open the solution i get "One or more projects in the solution were not loaded correctly" actually i get this on both solutions, so I tried to compile the source by myself (just adding all the files on the src folder to an empty project) and got errors with the files "old.c" and "server.c" so I deleted them to see what happens, it compiles succesfully, and when running with both cfg files and weights I get the weird results as @rap9430 or just a colored image, yellow or green rectangle.. does anyone experiences the same error or has some idea what I might be doing wrong? |
@richipower What version of MSVS, CUDA and OpenCV do you use?
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hello, @AlexeyAB and thank you for your very fast answer, i was trying this past days.. i am using MSVS 2015, CUDA 8, Opencv 2.4.13, still no success, (now trying v2) compiles succesfully (excluding CUDA and OpenCV) but maybe i am reading the wrong cfg/weight files(?), I tested with the documents provided from: https://github.com/AlexeyAB/darknet and downloaded the weights also from there, the problem now is that there are no predictions, even with threshold as zero.. |
@richipower About Yolo v2:
About Yolo v1: now it works propertly only on MSVS2013. |
After the update the latest changes you can use this in Yolo v2: To detection on image-file:
To detection on video-file:
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hello! I was testing with the video files, everything works flawless. Now I will check with the images, thank you for your support! :-) |
Current Yolo version 2 for Windows tested for custom training & detection: https://github.com/AlexeyAB/darknet |
Darknet compiles and runs correctly under window, but the yolo's result is not rational (see attached image). Is this a known issue? thanks.

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